Submission link: https://www.easychair.org/conferences/?conf=gamesec2017
Conference Topics:
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The goal of GameSec is to bring together academic and indus- trial
researchers in an effort to identify and discuss the major technical
challenges and recent results that highlight the connection between
game theory, control, distributed optimization, economic incentives
and real world security, reputation, trust and privacy problems in a
variety of technological systems. Submissions should solely be
original research papers that have neither been published nor
submitted for publication elsewhere.

* Game theory and mechanism design for security and privacy
* Pricing and economic incentives for building dependable and secure systems
* Dynamic control, learning, and optimization and approximation techniques
* Decision making and decision theory for cybersecurity and security requirements engineering
* Socio-technological and behavioral approaches to security
* Risk assessment and risk management
* Security investment and cyber insurance
* Security and privacy for the Internet-of-Things (IoT), cyber-physical systems, resilient control systems
* New approaches for security and privacy in cloud computing and for critical infrastructure
* Security and privacy of wireless and mobile communications, including user location privacy
* Game theory for intrusion detection
* Empirical and experimental studies with game-theoretic or optimization analysis for security and privacy

Special Track on “Data-Centric Models and Approaches”
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In cyber and physical security and privacy applications, data plays an
important role and presents fundamental challenges. In some domains, it is
difficult to gather a large amount of data, and the data available may suffer
from severe class imbalance, high noise, and numerous missing entries. In
other domains, when multiple agents are involved, how the data presented to
the agents impacts their decision making is under-explored. It can be
challenging to incorporate data of the available form into the game-theoretic
and decision-theoretic models for these domains, since many current approaches
apply to precisely defined models and how to define models using the available
data is unclear in many cases. In addition to the data-related challenges in
cyber and physical security domains, the use of data in many domains leads to
security and privacy concerns, and game-theoretic and decision-theoretic
models can be designed for addressing such concerns. This special track
invites submissions on various data-centric models and approaches, including
work on empirical game theory; adversarial machine learning; data collection
through crowdsourcing; synthetic data generation; applications of machine
learning methods; novel techniques for handling real-world data and evaluating
models using data.models and approaches, including work on empirical game
theory; adversarial machine learning; data collection through crowdsourcing;
synthetic data generation; applications of machine learning methods;
novel techniques for handling real-world data and evaluating models using data.